1. Field of Invention
The present invention relates to visions systems and related data processing.
2. Description of Related Art
Segmentation of images for vision data has become increasingly important for interpretation of scenes, particularly where specific surfaces (or classes of surfaces) are targets in an application. In this context, various roles for color vision have been proposed, including finding or discriminating edible fruits and leaves, facilitating scene and object recognition, and improving search under certain conditions. Additional applications include automatic segmenting of different types of tissue in medical images and automatic segmenting of targets in satellite photos. There has also been increasing interest within computer science in using color as a means of segmenting and identifying “meaningful regions” within a scene.
However, conventional approaches related to correlation methods and independent components analysis have been applied to these problems with limited success. Additionally, methods based on probability distributions (e.g., Bayesian analysis) are often based on assumptions for the underlying distributions that are not fully justified either in terms of the underlying data or in terms of matching the assumptions made by biological systems.
Thus, there is need for improved methods for segmentation of images, where vision-related information can be incorporated with limited modeling assumptions.